computational models learning (145 risultati)

Condizione: Good. Sticker on cover. Your purchase helps support Sri Lankan Children's Charity 'The Rainbow Centre'. Ex-library, so some wear and internal barcode may have been clipped, but in good overall condition. Our donations to The Rainbow Centre have helped provide an education and a safe haven to hundreds of children who live in appalling conditions.

Hardback. Condizione: Good. The book has been read but remains in clean condition. All pages are intact and the cover is intact. Some minor wear to the spine.

Broschiert. Condizione: Gut. 214 Seiten Das hier angebotene Buch stammt aus einer teilaufgelösten Bibliothek und kann die entsprechenden Kennzeichnungen aufweisen (Rückenschild, Instituts-Stempel.); der Buchzustand ist ansonsten ordentlich und dem Alter entsprechend gut. In ENGLISCHER Sprache. Sprache: Englisch Gewicht in Gramm: 385.

gebundene Ausgabe. Condizione: Gut. 466 Seiten; Das hier angebotene Buch stammt aus einer teilaufgelösten Bibliothek und kann die entsprechenden Kennzeichnungen aufweisen (Rückenschild, Instituts-Stempel.); der Buchzustand ist ansonsten ordentlich und dem Alter entsprechend gut. In ENGLISCHER Sprache. Sprache: Englisch Gewicht in Gramm: 925.

Condizione: Very Good. Shipped within 24 hours from our UK warehouse. Clean, undamaged book with no damage to pages and minimal wear to the cover. Spine still tight, in very good condition. Remember if you are not happy, you are covered by our 100% money back guarantee.

Condizione: as new. Cambridge, MA: The MIT Press, 1995. Paperback. 405 pp.- This is the third in a series of edited volumes exploring the evolving landscape of learning systems research which spans theory and experiment, symbols and signals. It continues the exploration of the synthesis of the machine learning subdisciplines begun in volumes I and II. The nineteen contributions cover learning theory, empirical comparisons of learning algorithms, the use of prior knowledge, probabilistic concepts, and the effect of variations over time in the concepts and feedback from the environment. The goal of this series is to explore the intersection of three historically distinct areas of learning research: computational learning theory, neural networks andAI machine learning. Although each field has its own conferences, journals, language, research, results, and directions, there is a growing intersection and effort to bring these fields into closer coordination. English text. Condition : as new. Condition : as new copy. ISBN 9780262660969. Keywords : ,

Condizione: Good. Ships from the UK. Former library book; may include library markings. Used book that is in clean, average condition without any missing pages.

Condizione: Gut. Auflage: New ed. 416 Seiten ex Library Book / aus einer wissenschafltichen Bibliothek / Sprache: Englisch Gewicht in Gramm: 969 22,1 x 14,7 x 2,5 cm, Taschenbuch.

Gebundene Ausgabe. Condizione: Gut. 208 Seiten Sofort verfügbar / Versand spätestens am nächsten Arbeitstag / Rechnung mit ausgewiesener MwSt. liegt bei / daily shipping worldwide with invoice / ex library in good condition / aus Bibliothek in guten Zustand/ Sprache: Englisch Gewicht in Gramm: 550.

Hardcover. Condizione: Très bon. Ancien livre de bibliothèque. Légères traces d'usure sur la couverture. Edition 1997. Ammareal reverse jusqu'à 15% du prix net de cet article à des organisations caritatives. ENGLISH DESCRIPTION Book Condition: Used, Very good. Former library book. Slight signs of wear on the cover. Edition 1997. Ammareal gives back up to 15% of this item's net price to charity organizations.

Condizione: Good. Most items will be dispatched the same or the next working day. A copy that has been read but remains in clean condition. All of the pages are intact and the cover is intact and the spine may show signs of wear. The book may have minor markings which are not specifically mentioned. A few small stains.

First edition. 318 pages. Cloth bound in near very good condition; Some wear to spine edges.

hardcover. Condizione: Very Good. Condizione sovraccoperta: very good. A nice copy. Clean text, solid binding. Dust Jacket protected by mylar cover.

Condizione: New.

Softcover. Condizione: Very Good+. First Edition. Light rubbing, small corner creases, spine slightly faded. ; Psychology Of Learning And Motivation, Vol 23; 8vo 8" - 9" tall.

Condizione: New. In.

Taschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - In recent years, machine learning has emerged as a significant area of research in artificial intelligence and cognitive science. At present, research in the field is being intensified from both the point of view of theory and of implementation, and the results are being introduced in practice. Machine learning has recently become the subject of interest of many young and talented scientists whose bold ideas have greatly contributed to the broadening of knowledge in this rapidly developing field of science. This situation has manifested itself in an increasing number of valuable contributions to scientific journals. However, such papers are necessarily compact descriptions of research problems. Computational Models of Learning supplements these contributions and is a collection of more extensive essays. These essays provide the reader with an increased knowledge of carefully selected problems of machine learning.

Condizione: Sehr gut. Zustand: Sehr gut | Seiten: 232 | Sprache: Englisch | Produktart: Bücher.

Condizione: New. In.

Condizione: New.

Softcover. Condizione: Très bon. Edition 2024. Ammareal reverse jusqu'à 15% du prix net de cet article à des organisations caritatives. ENGLISH DESCRIPTION Book Condition: Used, Very good. Edition 2024. Ammareal gives back up to 15% of this item's net price to charity organizations.

Hardcover. Condizione: Brand New. 240 pages. 9.25x6.10x9.49 inches. In Stock.

Condizione: New. In.

Buch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - Ensuring patient safety and security through cyberspace requires that all care professionals operate as a team and community . In order to be successful, it is of paramount importance that all members of the team have a shared understanding of the diagnosis, the condition of the patient, the secure use of medical devices and the plan of action. At present, to ensure that all mem bers have this 'shared mental model', members communicate and observe each other's actions. Based upon this information, members sho uld be able to confirm if indeed all have a shared mental model and speak up when deviations in one or more members and/or processes are suspected. From a group dynamical and information processing perspective, this verification process is known to be very vulnerable: how can red flags be detected in complicated surgery settings and do members feel psychologically safe enough to speak up when they have concerns about being on the same page as the rest of their team This book presents a new approach for saf ety and security through cyberspace through introducing a concept of co designed clinical pathways supported by the AI coach. The AI coach will be an intervention for both improving hospital wide safety and security through cyberspace. The AI Coach will empower users by supporting and facilitating the development of a shared mental model for team and organisational learning. The AI coach will function as an information, communication, cooperation and decision support system. The book advises to incorporate issues or cybersecurity risk management into the total safety and security process, among others through co-creating security.

Taschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - Although there is much literature on organisational learning, mathematical formalisation and computational simulation, there is no literature that uses mathematical modelling and simulation to represent and explore different facets of multilevel learning. This book provides an overview of recent work on mathematical formalisation and computational simulation of multilevel organisational learning by exploiting the possibilities of self-modeling network models to address it. This is the first book addressing mathematical formalisation and computational modeling of multilevel organisational learning in a systematic, principled manner. A self-modeling network modeling approach from AI and Network Science is used where in a reflective manner some of the network nodes (called self-model nodes) represent parts of the network's own network structure characteristics. This is supported by a dedicated software environment allowing to design and implement (higher-order) adaptive network models by specifying them in a conceptual manner at a high level of abstraction in a standard table format, without any need of algorithmic specification or programming. This modeling approach allows to model the development of knowledge in an organisational setting in a neatly structured manner at three different levels for the usage, adaptation and control, respectively, of the underlying mental models. Several examples of realistic cases of multilevel organisational learning are used to illustrate the approach. Crucial concepts such as the aggregation of mental models to form shared mental models out of individual mental models are addressed extensively. It is shown how to model context-sensitive control of organisational learning taking into account a wide variety of context factors, for example relating to levels of expertise of individuals or to leadership styles of managers involved. Mathematical equilibrium analysis of models of organisational learning is also addressed, among others allowing verification of correctness of the implemental models in comparison to their conceptual design.Chapters in this book also contribute to the Management and Business Sciences research by demonstrating how computational modeling can be used to capture complex management phenomena such as multilevel organizational learning. This book has a potential implication for practice by demonstrating how computational modeling can be used to capture learning scenarios, which then provide a basis for more informed managerial decisions.

Buch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - Although there is much literature on organisational learning, mathematical formalisation and computational simulation, there is no literature that uses mathematical modelling and simulation to represent and explore different facets of multilevel learning. This book provides an overview of recent work on mathematical formalisation and computational simulation of multilevel organisational learning by exploiting the possibilities of self-modeling network models to address it. This is the first book addressing mathematical formalisation and computational modeling of multilevel organisational learning in a systematic, principled manner. A self-modeling network modeling approach from AI and Network Science is used where in a reflective manner some of the network nodes (called self-model nodes) represent parts of the network's own network structure characteristics. This is supported by a dedicated software environment allowing to design and implement (higher-order) adaptive network models by specifying them in a conceptual manner at a high level of abstraction in a standard table format, without any need of algorithmic specification or programming. This modeling approach allows to model the development of knowledge in an organisational setting in a neatly structured manner at three different levels for the usage, adaptation and control, respectively, of the underlying mental models. Several examples of realistic cases of multilevel organisational learning are used to illustrate the approach. Crucial concepts such as the aggregation of mental models to form shared mental models out of individual mental models are addressed extensively. It is shown how to model context-sensitive control of organisational learning taking into account a wide variety of context factors, for example relating to levels of expertise of individuals or to leadership styles of managers involved. Mathematical equilibrium analysis of models of organisational learning is also addressed, among others allowing verification of correctness of the implemental models in comparison to their conceptual design.Chapters in this book also contribute to the Management and Business Sciences research by demonstrating how computational modeling can be used to capture complex management phenomena such as multilevel organizational learning. This book has a potential implication for practice by demonstrating how computational modeling can be used to capture learning scenarios, which then provide a basis for more informed managerial decisions.

Condizione: New. In.